About this Course

64,542 recent views
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Advanced Level
Approx. 32 hours to complete
English
Subtitles: English
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Advanced Level
Approx. 32 hours to complete
English
Subtitles: English

Offered by

University of Toronto logo

University of Toronto

Syllabus - What you will learn from this course

Week
1

Week 1

1 hour to complete

Welcome to Course 4: Motion Planning for Self-Driving Cars

1 hour to complete
4 videos (Total 18 min), 3 readings
4 videos
Welcome to the Course3m
Meet the Instructor, Steven Waslander5m
Meet the Instructor, Jonathan Kelly2m
3 readings
Course Readings10m
How to Use Discussion Forums15m
How to Use Supplementary Readings in This Course15m
2 hours to complete

Module 1: The Planning Problem

2 hours to complete
4 videos (Total 54 min), 1 reading, 1 quiz
4 videos
Lesson 2: Motion Planning Constraints13m
Lesson 3: Objective Functions for Autonomous Driving9m
Lesson 4: Hierarchical Motion Planning17m
1 reading
Module 1 Supplementary Reading10m
1 practice exercise
Module 1 Graded Quiz50m
Week
2

Week 2

6 hours to complete

Module 2: Mapping for Planning

6 hours to complete
5 videos (Total 50 min), 1 reading, 1 quiz
5 videos
Lesson 2: Populating Occupancy Grids from LIDAR Scan Data (Part 1)9m
Lesson 2: Populating Occupancy Grids from LIDAR Scan Data (Part 2)9m
Lesson 3: Occupancy Grid Updates for Self-Driving Cars9m
Lesson 4: High Definition Road Maps11m
1 reading
Module 2 Supplementary Reading1h
Week
3

Week 3

4 hours to complete

Module 3: Mission Planning in Driving Environments

4 hours to complete
3 videos (Total 35 min), 1 reading, 1 quiz
3 videos
Lesson 2: Dijkstra's Shortest Path Search10m
Lesson 3: A* Shortest Path Search13m
1 reading
Module 3 Supplementary Reading1h
1 practice exercise
Module 3 Graded Quiz50m
Week
4

Week 4

2 hours to complete

Module 4: Dynamic Object Interactions

2 hours to complete
3 videos (Total 36 min), 1 reading, 1 quiz
3 videos
Lesson 2: Map-Aware Motion Prediction11m
Lesson 3: Time to Collision12m
1 reading
Module 4 Supplementary Reading1h
1 practice exercise
Module 4 Graded Quiz50m

Reviews

TOP REVIEWS FROM MOTION PLANNING FOR SELF-DRIVING CARS

View all reviews

About the Self-Driving Cars Specialization

Be at the forefront of the autonomous driving industry. With market researchers predicting a $42-billion market and more than 20 million self-driving cars on the road by 2025, the next big job boom is right around the corner. This Specialization gives you a comprehensive understanding of state-of-the-art engineering practices used in the self-driving car industry. You'll get to interact with real data sets from an autonomous vehicle (AV)―all through hands-on projects using the open source simulator CARLA. Throughout your courses, you’ll hear from industry experts who work at companies like Oxbotica and Zoox as they share insights about autonomous technology and how that is powering job growth within the field. You’ll learn from a highly realistic driving environment that features 3D pedestrian modelling and environmental conditions. When you complete the Specialization successfully, you’ll be able to build your own self-driving software stack and be ready to apply for jobs in the autonomous vehicle industry. It is recommended that you have some background in linear algebra, probability, statistics, calculus, physics, control theory, and Python programming. You will need these specifications in order to effectively run the CARLA simulator: Windows 7 64-bit (or later) or Ubuntu 16.04 (or later), Quad-core Intel or AMD processor (2.5 GHz or faster), NVIDIA GeForce 470 GTX or AMD Radeon 6870 HD series card or higher, 8 GB RAM, and OpenGL 3 or greater (for Linux computers)....
Self-Driving Cars

Frequently Asked Questions

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

  • This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.

More questions? Visit the Learner Help Center.